A general quasi-automatic initialization for snakes: application to ultrasound images
Clovis Tauber, Hadj Batatia, Alain Ayache · 2005
Segmentation with active contours is heavily dependent on the initialization. In this paper we propose a novel method for a quasi-automatic initialization of deformable models. Our method relies on the use of an additional energy based on the gradient vector flow. We define the centers of strong and weak divergence and use them to set up the initial curve. As our goal is the segmentation of the heart cavities, we also propose a new gradient vector field for ultrasound images based on the coefficient of variation. Results on real ultra-sound images are presented and compared to the boundaries manually outlined by an expert. They confirm the potential of the method.